OBJECTIVE: To compare the results of two different survey sampling techniques (cluster and systematic) used to measure retrospective mortality on the same population at about the same time. METHODS: Immediately following a cluster survey to assess mortality retrospectively in a town in North Darfur, Sudan in 2005, we conducted a systematic survey on the same population and again measured mortality retrospectively. This was only possible because the geographical layout of the town, and the availability of a good previous estimate of the population size and distribution, were conducive to the systematic survey design. RESULTS: Both the cluster and the systematic survey methods gave similar results below the emergency threshold for crude mortality (0.80 versus 0.77 per 10,000/day, respectively). The results for mortality in children under 5 years old (U5MR) were different (1.16 versus 0.71 per 10,000/day), although this difference was not statistically significant. The 95% confidence intervals were wider in each case for the cluster survey, especially for the U5MR (0.15-2.18 for the cluster versus 0.09-1.33 for the systematic survey). CONCLUSION: Both methods gave similar age and sex distributions. The systematic survey, however, allowed for an estimate of the town's population size, and a smaller sample could have been used. This study was conducted in a purely operational, rather than a research context. A research study into alternative methods for measuring retrospective mortality in areas with mortality significantly above the emergency threshold is needed, and is planned for 2006.

In two-stage cluster surveys, the traditional method used in second-stage sampling (in which the first household in a cluster is selected) is time-consuming and may result in biased estimates of the indicator of interest. Firstly, a random direction from the center of the cluster is selected, usually by spinning a pen. The houses along that direction are then counted out to the boundary of the cluster, and one is then selected at random to be the first household surveyed. This process favors households towards the center of the cluster, but it could easily be improved. During a recent meningitis vaccination coverage survey in Maradi, Niger, we compared this method of first household selection to two alternatives in urban zones: 1) using a superimposed grid on the map of the cluster area and randomly selecting an intersection; and 2) drawing the perimeter of the cluster area using a Global Positioning System (GPS) and randomly selecting one point within the perimeter. Although we only compared a limited number of clusters using each method, we found the sampling grid method to be the fastest and easiest for field survey teams, although it does require a map of the area. Selecting a random GPS point was also found to be a good method, once adequate training can be provided. Spinning the pen and counting households to the boundary was the most complicated and time-consuming. The two methods tested here represent simpler, quicker and potentially more robust alternatives to spinning the pen for cluster surveys in urban areas. However, in rural areas, these alternatives would favor initial household selection from lower density (or even potentially empty) areas. Bearing in mind these limitations, as well as available resources and feasibility, investigators should choose the most appropriate method for their particular survey context.

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